This invention relates to the problem of dynamic bandwidth allocation over passive optical networks. It arbitrates the upstream channel bandwidth among multiple optical network units (ONUs). In addition, this invention relates to the problem of service differentiation over passive optical networks (PONs). It integrates queuing, scheduling, and class-based bandwidth allocation to serve diverse end users. Specifically, the basic limited sharing with traffic prediction (LSTP) scheme is extended to serve the classified network traffic over broadband PONs (EPONs, BPONs, GPONs).
Passive optical networks (PONs) address the first mile of the communication infrastructure between the service provider central offices and the customer sites, also known as the “access network.” With the expansion of services offered over the Internet, a dramatic increase of bandwidth has been facilitated in the backbone network through the use of wavelength division multiplexing (WDM), providing tens of Gigabits per second per wavelength. At the same time, the local area networks (LANs) have been scaled up from 10 Mbps to 100 Mbps and are being upgraded to Gigabit Ethernets. Such a growing gap between the capacity of the backbone network and the end users' needs results in the serious bottleneck of the access network in between [3]. It is desired to have access network technology that can provide low cost and efficient equipment to facilitate multi-service access to the end users. PONs are considered as an attractive and promising solution to the broadband subscriber access network. As an inexpensive, simple, and scalable technology, and with the capability of delivering integrated services, PONs are deliberated in the standardization process of the IEEE 802.3ah Ethernet in the First Mile (EFM) Task Force [1] and ITU-T Study Group 15 [2], which aim to significantly increase the broadband service performance while minimizing equipment, operation, and maintenance costs.
As a low-cost, high-speed technology, and with the recent approval of PON standards IEEE 802.3ah, ITU-T G.983x, and ITU-T G.984x, PONs are an attractive and promising solution to the broadband subscriber access network. As illustrated in FIG. 1, a PON consists of an optical line terminal (OLT) located at the provider central office and a set of associated optical network units (ONUs) that deliver broadband services to the end users. A single fiber extends from an OLT to a 1:N passive optical splitter, which fans out multiple single fiber drops to different ONUs. The active electronic components in the traditional access networks, such as regenerators and amplifiers, are eliminated in PONs and replaced with the less expensive passive optical splitters, which are simpler and easier to maintain. A major feature of PONs is the utility of a shared upstream channel among multiple ONUs, and thus bandwidth management is a critical issue in order to improve the PON efficiency. The existing bandwidth allocation schemes pose some critical limitations. One of the major problems is that the upstream data arriving during the waiting time cannot be delivered in the next timeslot, thus posing additional data delay, severe data loss, and longer queue size. These are the barriers to achieving high bandwidth efficiency over broadband access networks. As a result, known available bandwidth allocation schemes are inefficient over these networks.
Since the access network is required to accommodate various kinds of traffic, service differentiation is a distinguished feature that PONs are expected to provide. Owing to the differences in subscriber's service level agreements (SLAs), different end users may have different bandwidth requirements. A pragmatic approach is to employ timeslot-based bandwidth allocation by providing various lengths of timeslots to serve different traffic. The existing service differentiation schemes pose some critical limitations. The major problems include how to enqueue and schedule the local traffic, and how to allocate the upstream bandwidth to different queues. Available service differentiation schemes only tackle part of the problem, and they are inefficient for delivering diverse traffic over PONs.
Data are broadcasted from the OLT downstream to the ONUs using the entire bandwidth of the downstream channel. ONUs selectively receive data destined for them by matching the carried destination addresses.
The process of transporting data upstream to the OLT over PONs is different from that of transporting data downstream to the local users. In the upstream direction, a different channel wavelength is employed for the upstream traffic, and multiple ONUs share this common upstream channel. Therefore, only a single ONU may transmit during a timeslot in order to avoid data collisions. Data from local users are first buffered at an ONU until the exclusively assigned timeslot arrives. The buffered data would be “bursted” out to the OLT in the timeslot at the full channel speed.
In order to provide diverse quality of service (QoS), the bandwidth management of the upstream channel is a critical issue for the successful implementation of PONs. Different PON technologies have their own MAC control messages to facilitate the upstream bandwidth allocation. For example, EPONs adopt MultiPoint Control Protocol (MPCP) [1] developed by the IEEE 802.3ah EFM Task Force. The REPORT message is used by the ONU to report the bandwidth requirement to the OLT, while the GATE message is used by the OLT to assign the timeslot for a specific ONU. There have been numerous proposals in the literature to tackle the upstream bandwidth allocation.
The limited bandwidth allocation (LBA) [3] scheme grants an ONU the requested timeslot length, but no more than an upper bound. The bandwidth guaranteed polling (BGP) scheme [4] allocates the timeslot to an ONU according to its service level agreement (SLA). Choi and Huh [5] proposed the classified bandwidth allocation for multimedia services. However, the BGP scheme is incompatible with the PON standard and would not be standardized. The LBA scheme and the Choi and Huh scheme do not consider the incoming data during the ONU waiting time, which ranges from sending the queue length report to sending the buffered data, and thus, such data have to be deferred to the next timeslot, posing additional delay and loss.
Assi et al. [6] predicted such incoming data of the high priority traffic in a rough way by simply replacing it with the actual number of incoming data during the last waiting time. The drawback is that the service order of ONUs changes drastically, with the heavily loaded ONUs always being served after the lightly loaded ones, and therefore, the prediction of the incoming high priority traffic is severely impaired because the waiting time of each ONU may change drastically.